postgres-optimization

What problem does it solve?

Manually optimizing PostgreSQL databases is complex, time-consuming, and often requires deep expertise. Slow queries and inefficient indexing can severely impact application performance and user experience. This skill automates the process, combining past learnings with live analysis.

Core Features & Use Cases

• Memory-Augmented Research: Leverages past optimization successes and failures from institutional memory to inform current strategies, preventing repeated mistakes.
• Live Database Analysis: Uses postgres-mcp tools to perform comprehensive health checks, identify slow queries, analyze execution plans, and recommend optimal indexes.
• Intelligent Synthesis & Recommendation: Combines historical knowledge with real-time database data to propose actionable, verified optimization strategies, complete with expected performance impacts.
• Use Case: When a user reports "My query to find users by email is very slow", the skill will search past optimizations, analyze the current database health and query plan, recommend a specific index, test its impact hypothetically, and, upon approval, execute and document the change.

Quick Start

Optimize my PostgreSQL database for slow queries. The skill will analyze your database, suggest improvements, and ask for approval before making changes.